High frequency sensor data analysis and integration with low frequency sensor data used for parametric data modeling for model based reasoners

Abstract

A method implemented by a computing system identifies anomalies that represents potential off-normal behavior of components on an aircraft based on data from sensors during various modes of operations including in-flight operation of the aircraft. High-frequency sensor outputs monitor performance parameters of respective components. Anomaly criteria is dynamically selected and the high-frequency sensor outputs are compared with the anomaly criteria where the comparison results determine whether potentially off-normal behavior exists. A conditional anomaly tag is inserted in the digitized representations of first high-frequency sensor outputs where the corresponding comparison results indicate potentially off-normal behavior. At least the digitized representations of the first high-frequency sensor outputs containing the conditional anomaly tag are sent to a computer-based diagnostic system for a final determination of whether the conditional anomaly tag associated with the respective components represents off-normal behavior for the respective components.